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Record Nr. |
UNINA9910481960203321 |
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Autore |
Piunovskiy Alexey |
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Titolo |
Continuous-Time Markov Decision Processes : Borel Space Models and General Control Strategies / / by Alexey Piunovskiy, Yi Zhang |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XXIV, 583 p. 10 illus., 3 illus. in color.) |
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Collana |
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Probability Theory and Stochastic Modelling, , 2199-3149 ; ; 97 |
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Disciplina |
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Soggetti |
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Probabilities |
Mathematical statistics - Data processing |
System theory |
Control theory |
Mathematical optimization |
Probability Theory |
Statistics and Computing |
Systems Theory, Control |
Optimization |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Foreword -- Preface -- Description of CTMDPs and Preliminaries -- Selected Properties of Controlled Processes -- The Discounted Cost Model -- Reduction to DTMDP: The Total Cost Model -- The Average Cost Model -- The Total Cost Model: General Case -- Gradual-Impulsive Control Models -- Appendices: Miscellaneous Results.-Relevant Definitions and Facts -- Definitions and Facts about Discrete-Time Markov Decision Processes -- Bibliography -- Index -- Notation. . |
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Sommario/riassunto |
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This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on |
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dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable. . |
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